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基于最大熵概念的復(fù)雜隨機變量統(tǒng)計模型
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    摘要:

    基于最大熵概念的隨機變量統(tǒng)計模型,能得到最少偏見的隨機變量的概率分布。建立了汽車發(fā)動機和離合器隨機工作載荷的基于最大熵概念的概率密度函數(shù)統(tǒng)計模型,。示例表明,,基于最大熵概念上的隨機變量統(tǒng)計模型是可行,、有效的。

    Abstract:

    The statistical distribution of random variables is absolutely necessary in many engineering practices, such as reliability analysis, fatigue life test. When building a statistical model, in general, a hypothesis was proposed based on statistical data of samples and experience of the engineer, who took the responsibility. Therefore the hypothesis of the statistical model would be influenced by the opinion of the engineer. Based on maximum entropy concept, statistical model of complicated random variables was presented, and a parameter estimation method of the distribution function was also proposed. Maximum entropy statistical models were used to describe service loads of engine and clutch of a light truck, and rotating speed. The result showed that this model is feasible and valid.

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高翔,鄭建祥.基于最大熵概念的復(fù)雜隨機變量統(tǒng)計模型[J].農(nóng)業(yè)機械學(xué)報,2008,39(2):43-46.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(2):43-46.

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